from sklearn_benchmarks.reporting.hp_match import HpMatchReporting
import pandas as pd
pd.set_option('display.max_colwidth', None)
pd.set_option('display.max_columns', None)
pd.set_option('display.max_rows', None)
measurements = ['iteration_throughput', 'latency', 'mean_duration_sklearn', 'mean_duration_sklearnex', 'speedup', 'std_duration_sklearn', 'std_duration_sklearnex', 'std_speedup']
def get_position(string):
if "mean_duration" in string:
return 3
elif "std_duration" in string:
return 2
elif "score" in string:
return 1
elif "speedup" in string:
return 0
else:
return -1
sorted(measurements, key=get_position, reverse=True)
['mean_duration_sklearn', 'mean_duration_sklearnex', 'std_duration_sklearn', 'std_duration_sklearnex', 'speedup', 'std_speedup', 'iteration_throughput', 'latency']
reporting = HpMatchReporting(against_lib="sklearnex", config="config.yml", log_scale=True)
reporting.make_report()
We assume here there is a perfect match between the hyperparameters of both librairies. For a given set of parameters and a given dataset, we compute the speedup
time scikit-learn / time sklearnex. For instance, a speedup of 2 means that sklearnex is twice as fast as scikit-learn for a given set of parameters and a given dataset.
KNeighborsClassifier_brute_force¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: algorithm=brute.
| estimator | function | n_samples_train | n_samples | n_features | parameters_digest | dataset_digest | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | algorithm | n_jobs | n_neighbors | accuracy_score_sklearn | mean_duration_sklearnex | std_duration_sklearnex | accuracy_score_sklearnex | speedup | std_speedup | diff_accuracy_scores | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | e70d8e7886766d41f30889506baa1e67 | 2cf49829391aa7891e877f2ed070adf0 | 2.027753 | 0.260970 | NaN | 0.000395 | 0.002028 | brute | -1 | 1 | 0.663 | 0.401495 | 0.008845 | 0.687 | 5.050505 | 5.051730 | 0.024 |
| 4 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 22d5eac4a4146149b35eae6914921514 | 2cf49829391aa7891e877f2ed070adf0 | 2.776739 | 0.044499 | NaN | 0.000288 | 0.002777 | brute | -1 | 5 | 0.757 | 0.392266 | 0.006000 | 0.742 | 7.078715 | 7.079543 | 0.015 |
| 7 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 16f94fc93942ff7ece860c9b0f64645f | 2cf49829391aa7891e877f2ed070adf0 | 2.158312 | 0.024728 | NaN | 0.000371 | 0.002158 | brute | 1 | 100 | 0.882 | 0.458089 | 0.008246 | 0.875 | 4.711559 | 4.712322 | 0.007 |
| 8 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 16f94fc93942ff7ece860c9b0f64645f | 2cf49829391aa7891e877f2ed070adf0 | 0.023255 | 0.000925 | NaN | 0.000034 | 0.023255 | brute | 1 | 100 | 1.000 | 0.011583 | 0.001696 | 0.000 | 2.007716 | 2.029136 | 1.000 |
| 10 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2d5f2b2c02d77766434d9e5033b4a76c | 2cf49829391aa7891e877f2ed070adf0 | 2.758314 | 0.045003 | NaN | 0.000290 | 0.002758 | brute | -1 | 100 | 0.882 | 0.444168 | 0.005463 | 0.875 | 6.210074 | 6.210544 | 0.007 |
| 11 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 2d5f2b2c02d77766434d9e5033b4a76c | 2cf49829391aa7891e877f2ed070adf0 | 0.024451 | 0.001874 | NaN | 0.000033 | 0.024451 | brute | -1 | 100 | 1.000 | 0.010426 | 0.000624 | 0.000 | 2.345216 | 2.349416 | 1.000 |
| 13 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | efac583623711d395ddae7a1e881ff68 | 2cf49829391aa7891e877f2ed070adf0 | 2.131869 | 0.024922 | NaN | 0.000375 | 0.002132 | brute | 1 | 5 | 0.757 | 0.398827 | 0.006950 | 0.742 | 5.345351 | 5.346162 | 0.015 |
| 16 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | b79d63bb7670c492de5c3befac58fe29 | 2cf49829391aa7891e877f2ed070adf0 | 1.345079 | 0.016867 | NaN | 0.000595 | 0.001345 | brute | 1 | 1 | 0.663 | 0.389310 | 0.006047 | 0.687 | 3.455032 | 3.455449 | 0.024 |
| 19 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | e70d8e7886766d41f30889506baa1e67 | 88843f54689e3271092f70126e1de585 | 1.637761 | 0.036030 | NaN | 0.000010 | 0.001638 | brute | -1 | 1 | 0.896 | 0.083410 | 0.002690 | 0.967 | 19.634964 | 19.645175 | 0.071 |
| 22 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 22d5eac4a4146149b35eae6914921514 | 88843f54689e3271092f70126e1de585 | 2.464218 | 0.055673 | NaN | 0.000006 | 0.002464 | brute | -1 | 5 | 0.922 | 0.085323 | 0.003310 | 0.974 | 28.881189 | 28.902909 | 0.052 |
| 25 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 16f94fc93942ff7ece860c9b0f64645f | 88843f54689e3271092f70126e1de585 | 1.907462 | 0.016050 | NaN | 0.000008 | 0.001907 | brute | 1 | 100 | 0.929 | 0.135446 | 0.004620 | 0.975 | 14.082832 | 14.091020 | 0.046 |
| 28 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 2d5f2b2c02d77766434d9e5033b4a76c | 88843f54689e3271092f70126e1de585 | 2.472077 | 0.029250 | NaN | 0.000006 | 0.002472 | brute | -1 | 100 | 0.929 | 0.133449 | 0.004922 | 0.975 | 18.524440 | 18.537036 | 0.046 |
| 31 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | efac583623711d395ddae7a1e881ff68 | 88843f54689e3271092f70126e1de585 | 1.918974 | 0.019640 | NaN | 0.000008 | 0.001919 | brute | 1 | 5 | 0.922 | 0.083788 | 0.001841 | 0.974 | 22.902687 | 22.908213 | 0.052 |
| 34 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | b79d63bb7670c492de5c3befac58fe29 | 88843f54689e3271092f70126e1de585 | 1.105213 | 0.014106 | NaN | 0.000014 | 0.001105 | brute | 1 | 1 | 0.896 | 0.083515 | 0.003586 | 0.967 | 13.233668 | 13.245863 | 0.071 |
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | iteration_throughput | latency | n_jobs | n_neighbors | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.012 | 0.001 | 6.665 | 0.0 | -1 | 1 | 0.050 | 0.006 | 0.241 | 0.242 | See | See |
| 3 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.012 | 0.000 | 6.621 | 0.0 | -1 | 5 | 0.051 | 0.003 | 0.236 | 0.236 | See | See |
| 6 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.012 | 0.001 | 6.541 | 0.0 | 1 | 100 | 0.051 | 0.002 | 0.242 | 0.242 | See | See |
| 9 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.013 | 0.001 | 6.265 | 0.0 | -1 | 100 | 0.051 | 0.002 | 0.251 | 0.251 | See | See |
| 12 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.012 | 0.000 | 6.777 | 0.0 | 1 | 5 | 0.048 | 0.001 | 0.245 | 0.245 | See | See |
| 15 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.013 | 0.001 | 6.194 | 0.0 | 1 | 1 | 0.049 | 0.001 | 0.263 | 0.263 | See | See |
| 18 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.005 | 0.000 | 0.350 | 0.0 | -1 | 1 | 0.009 | 0.000 | 0.506 | 0.507 | See | See |
| 21 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.005 | 0.000 | 0.348 | 0.0 | -1 | 5 | 0.009 | 0.001 | 0.523 | 0.526 | See | See |
| 24 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.005 | 0.000 | 0.348 | 0.0 | 1 | 100 | 0.009 | 0.000 | 0.525 | 0.526 | See | See |
| 27 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.005 | 0.000 | 0.344 | 0.0 | -1 | 100 | 0.009 | 0.001 | 0.533 | 0.541 | See | See |
| 30 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.005 | 0.001 | 0.352 | 0.0 | 1 | 5 | 0.008 | 0.000 | 0.540 | 0.540 | See | See |
| 33 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.004 | 0.000 | 0.356 | 0.0 | 1 | 1 | 0.009 | 0.000 | 0.516 | 0.517 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | iteration_throughput | latency | n_jobs | n_neighbors | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2.028 | 0.261 | 0.000 | 0.002 | -1 | 1 | 0.401 | 0.009 | 5.051 | 5.052 | See | See |
| 2 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.026 | 0.002 | 0.000 | 0.026 | -1 | 1 | 0.011 | 0.001 | 2.448 | 2.452 | See | See |
| 4 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2.777 | 0.044 | 0.000 | 0.003 | -1 | 5 | 0.392 | 0.006 | 7.079 | 7.080 | See | See |
| 5 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.025 | 0.002 | 0.000 | 0.025 | -1 | 5 | 0.010 | 0.000 | 2.382 | 2.383 | See | See |
| 7 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2.158 | 0.025 | 0.000 | 0.002 | 1 | 100 | 0.458 | 0.008 | 4.712 | 4.712 | See | See |
| 8 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.023 | 0.001 | 0.000 | 0.023 | 1 | 100 | 0.012 | 0.002 | 2.008 | 2.029 | See | See |
| 10 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2.758 | 0.045 | 0.000 | 0.003 | -1 | 100 | 0.444 | 0.005 | 6.210 | 6.211 | See | See |
| 11 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.024 | 0.002 | 0.000 | 0.024 | -1 | 100 | 0.010 | 0.001 | 2.345 | 2.349 | See | See |
| 13 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2.132 | 0.025 | 0.000 | 0.002 | 1 | 5 | 0.399 | 0.007 | 5.345 | 5.346 | See | See |
| 14 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.023 | 0.001 | 0.000 | 0.023 | 1 | 5 | 0.011 | 0.001 | 2.026 | 2.034 | See | See |
| 16 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 1.345 | 0.017 | 0.001 | 0.001 | 1 | 1 | 0.389 | 0.006 | 3.455 | 3.455 | See | See |
| 17 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.021 | 0.001 | 0.000 | 0.021 | 1 | 1 | 0.011 | 0.001 | 1.933 | 1.937 | See | See |
| 19 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 1.638 | 0.036 | 0.000 | 0.002 | -1 | 1 | 0.083 | 0.003 | 19.635 | 19.645 | See | See |
| 20 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.005 | 0.003 | 0.000 | 0.005 | -1 | 1 | 0.001 | 0.000 | 9.485 | 9.535 | See | See |
| 22 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 2.464 | 0.056 | 0.000 | 0.002 | -1 | 5 | 0.085 | 0.003 | 28.881 | 28.903 | See | See |
| 23 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.007 | 0.002 | 0.000 | 0.007 | -1 | 5 | 0.001 | 0.000 | 11.436 | 11.505 | See | See |
| 25 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 1.907 | 0.016 | 0.000 | 0.002 | 1 | 100 | 0.135 | 0.005 | 14.083 | 14.091 | See | See |
| 26 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.003 | 0.000 | 0.000 | 0.003 | 1 | 100 | 0.001 | 0.000 | 4.129 | 4.297 | See | See |
| 28 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 2.472 | 0.029 | 0.000 | 0.002 | -1 | 100 | 0.133 | 0.005 | 18.524 | 18.537 | See | See |
| 29 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.009 | 0.002 | 0.000 | 0.009 | -1 | 100 | 0.001 | 0.000 | 13.829 | 13.939 | See | See |
| 31 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 1.919 | 0.020 | 0.000 | 0.002 | 1 | 5 | 0.084 | 0.002 | 22.903 | 22.908 | See | See |
| 32 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.003 | 0.000 | 0.000 | 0.003 | 1 | 5 | 0.001 | 0.000 | 5.088 | 5.131 | See | See |
| 34 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 1.105 | 0.014 | 0.000 | 0.001 | 1 | 1 | 0.084 | 0.004 | 13.234 | 13.246 | See | See |
| 35 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.002 | 0.000 | 0.000 | 0.002 | 1 | 1 | 0.001 | 0.000 | 3.045 | 3.137 | See | See |
KNeighborsClassifier_kd_tree¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: algorithm=kd_tree.
| estimator | function | n_samples_train | n_samples | n_features | parameters_digest | dataset_digest | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | algorithm | n_jobs | n_neighbors | accuracy_score_sklearn | mean_duration_sklearnex | std_duration_sklearnex | accuracy_score_sklearnex | speedup | std_speedup | diff_accuracy_scores | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | fe8267e25dadb302ed498e50fabf7ef4 | 1eb6cf1a720a225efb91df0b529b0510 | 0.882532 | 1.124641 | NaN | 0.000091 | 0.000883 | kd_tree | -1 | 1 | 0.929 | 0.125178 | 0.004629 | 0.910 | 7.050240 | 7.055060 | 0.019 |
| 4 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | dc74b969bf622bc24ba3bc62c980983b | 1eb6cf1a720a225efb91df0b529b0510 | 1.098293 | 0.383205 | NaN | 0.000073 | 0.001098 | kd_tree | -1 | 5 | 0.946 | 0.221112 | 0.003932 | 0.941 | 4.967132 | 4.967917 | 0.005 |
| 7 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 41accfcdcd5c50784bedf6164b63de99 | 1eb6cf1a720a225efb91df0b529b0510 | 5.737746 | 0.794953 | NaN | 0.000014 | 0.005738 | kd_tree | 1 | 100 | 0.951 | 0.684492 | 0.015340 | 0.940 | 8.382492 | 8.384597 | 0.011 |
| 10 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 022f7445d43bb1dbc24dc3106c03cb93 | 1eb6cf1a720a225efb91df0b529b0510 | 3.216986 | 0.250691 | NaN | 0.000025 | 0.003217 | kd_tree | -1 | 100 | 0.951 | 0.672461 | 0.005641 | 0.940 | 4.783899 | 4.784067 | 0.011 |
| 13 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 84622ba45e941db642965553529e1941 | 1eb6cf1a720a225efb91df0b529b0510 | 1.659354 | 0.213759 | NaN | 0.000048 | 0.001659 | kd_tree | 1 | 5 | 0.946 | 0.228686 | 0.005619 | 0.941 | 7.256027 | 7.258217 | 0.005 |
| 16 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | a9455565db1d8e052a783317c99744ff | 1eb6cf1a720a225efb91df0b529b0510 | 0.936813 | 0.277644 | NaN | 0.000085 | 0.000937 | kd_tree | 1 | 1 | 0.929 | 0.125561 | 0.003632 | 0.910 | 7.461034 | 7.464154 | 0.019 |
| 19 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | fe8267e25dadb302ed498e50fabf7ef4 | edf7cb014c2c0910e1c3aaaf8ae633f2 | 0.035003 | 0.014955 | NaN | 0.000457 | 0.000035 | kd_tree | -1 | 1 | 0.891 | 0.000486 | 0.000024 | 0.879 | 72.042404 | 72.132716 | 0.012 |
| 22 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | dc74b969bf622bc24ba3bc62c980983b | edf7cb014c2c0910e1c3aaaf8ae633f2 | 0.031504 | 0.004727 | NaN | 0.000508 | 0.000032 | kd_tree | -1 | 5 | 0.911 | 0.000826 | 0.000059 | 0.905 | 38.129740 | 38.227709 | 0.006 |
| 25 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 41accfcdcd5c50784bedf6164b63de99 | edf7cb014c2c0910e1c3aaaf8ae633f2 | 0.043169 | 0.011873 | NaN | 0.000371 | 0.000043 | kd_tree | 1 | 100 | 0.894 | 0.005372 | 0.000384 | 0.917 | 8.036307 | 8.056851 | 0.023 |
| 28 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 022f7445d43bb1dbc24dc3106c03cb93 | edf7cb014c2c0910e1c3aaaf8ae633f2 | 0.047777 | 0.007131 | NaN | 0.000335 | 0.000048 | kd_tree | -1 | 100 | 0.894 | 0.007168 | 0.002199 | 0.917 | 6.664937 | 6.971576 | 0.023 |
| 31 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 84622ba45e941db642965553529e1941 | edf7cb014c2c0910e1c3aaaf8ae633f2 | 0.027488 | 0.001631 | NaN | 0.000582 | 0.000027 | kd_tree | 1 | 5 | 0.911 | 0.000826 | 0.000125 | 0.905 | 33.286679 | 33.668114 | 0.006 |
| 34 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | a9455565db1d8e052a783317c99744ff | edf7cb014c2c0910e1c3aaaf8ae633f2 | 0.025897 | 0.001193 | NaN | 0.000618 | 0.000026 | kd_tree | 1 | 1 | 0.891 | 0.000510 | 0.000014 | 0.879 | 50.813088 | 50.833015 | 0.012 |
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | iteration_throughput | latency | n_jobs | n_neighbors | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 2.844 | 0.046 | 0.028 | 0.0 | -1 | 1 | 0.779 | 0.047 | 3.651 | 3.657 | See | See |
| 3 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 4.413 | 0.068 | 0.018 | 0.0 | -1 | 5 | 0.746 | 0.012 | 5.914 | 5.915 | See | See |
| 6 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 4.395 | 0.042 | 0.018 | 0.0 | 1 | 100 | 0.731 | 0.045 | 6.013 | 6.024 | See | See |
| 9 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 4.387 | 0.056 | 0.018 | 0.0 | -1 | 100 | 0.759 | 0.012 | 5.778 | 5.779 | See | See |
| 12 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 4.472 | 0.085 | 0.018 | 0.0 | 1 | 5 | 0.720 | 0.017 | 6.210 | 6.212 | See | See |
| 15 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 4.419 | 0.056 | 0.018 | 0.0 | 1 | 1 | 0.749 | 0.008 | 5.899 | 5.899 | See | See |
| 18 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.001 | 0.021 | 0.0 | -1 | 1 | 0.004 | 0.003 | 0.184 | 0.238 | See | See |
| 21 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.001 | 0.015 | 0.0 | -1 | 5 | 0.002 | 0.002 | 0.636 | 0.977 | See | See |
| 24 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | 0.023 | 0.0 | 1 | 100 | 0.001 | 0.001 | 0.540 | 0.661 | See | See |
| 27 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | 0.023 | 0.0 | -1 | 100 | 0.001 | 0.000 | 0.657 | 0.673 | See | See |
| 30 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | 0.023 | 0.0 | 1 | 5 | 0.001 | 0.000 | 0.734 | 0.736 | See | See |
| 33 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | 0.027 | 0.0 | 1 | 1 | 0.001 | 0.000 | 0.623 | 0.628 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | iteration_throughput | latency | n_jobs | n_neighbors | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 0.883 | 1.125 | 0.000 | 0.001 | -1 | 1 | 0.125 | 0.005 | 7.050 | 7.055 | See | See |
| 2 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.003 | 0.001 | 0.000 | 0.003 | -1 | 1 | 0.000 | 0.000 | 12.042 | 12.297 | See | See |
| 4 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 1.098 | 0.383 | 0.000 | 0.001 | -1 | 5 | 0.221 | 0.004 | 4.967 | 4.968 | See | See |
| 5 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.004 | 0.002 | 0.000 | 0.004 | -1 | 5 | 0.001 | 0.000 | 7.483 | 8.147 | See | See |
| 7 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 5.738 | 0.795 | 0.000 | 0.006 | 1 | 100 | 0.684 | 0.015 | 8.382 | 8.385 | See | See |
| 8 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.003 | 0.001 | 0.000 | 0.003 | 1 | 100 | 0.001 | 0.000 | 3.304 | 3.576 | See | See |
| 10 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 3.217 | 0.251 | 0.000 | 0.003 | -1 | 100 | 0.672 | 0.006 | 4.784 | 4.784 | See | See |
| 11 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.006 | 0.001 | 0.000 | 0.006 | -1 | 100 | 0.001 | 0.000 | 7.552 | 7.740 | See | See |
| 13 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 1.659 | 0.214 | 0.000 | 0.002 | 1 | 5 | 0.229 | 0.006 | 7.256 | 7.258 | See | See |
| 14 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.002 | 0.000 | 0.000 | 0.002 | 1 | 5 | 0.000 | 0.000 | 3.675 | 3.830 | See | See |
| 16 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 0.937 | 0.278 | 0.000 | 0.001 | 1 | 1 | 0.126 | 0.004 | 7.461 | 7.464 | See | See |
| 17 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.001 | 0.000 | 0.000 | 0.001 | 1 | 1 | 0.000 | 0.000 | 3.979 | 4.114 | See | See |
| 19 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.035 | 0.015 | 0.000 | 0.000 | -1 | 1 | 0.000 | 0.000 | 72.042 | 72.133 | See | See |
| 20 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.003 | 0.000 | 0.000 | 0.003 | -1 | 1 | 0.000 | 0.000 | 23.387 | 23.615 | See | See |
| 22 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.032 | 0.005 | 0.001 | 0.000 | -1 | 5 | 0.001 | 0.000 | 38.130 | 38.228 | See | See |
| 23 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.002 | 0.000 | 0.000 | 0.002 | -1 | 5 | 0.000 | 0.000 | 18.156 | 18.371 | See | See |
| 25 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.043 | 0.012 | 0.000 | 0.000 | 1 | 100 | 0.005 | 0.000 | 8.036 | 8.057 | See | See |
| 26 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.001 | 0.000 | 0.000 | 0.001 | 1 | 100 | 0.000 | 0.000 | 4.641 | 4.800 | See | See |
| 28 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.048 | 0.007 | 0.000 | 0.000 | -1 | 100 | 0.007 | 0.002 | 6.665 | 6.972 | See | See |
| 29 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.002 | 0.000 | 0.000 | 0.002 | -1 | 100 | 0.000 | 0.000 | 16.437 | 16.549 | See | See |
| 31 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.027 | 0.002 | 0.001 | 0.000 | 1 | 5 | 0.001 | 0.000 | 33.287 | 33.668 | See | See |
| 32 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.001 | 0.000 | 0.000 | 0.001 | 1 | 5 | 0.000 | 0.000 | 5.352 | 5.390 | See | See |
| 34 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.026 | 0.001 | 0.001 | 0.000 | 1 | 1 | 0.001 | 0.000 | 50.813 | 50.833 | See | See |
| 35 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.001 | 0.000 | 0.000 | 0.001 | 1 | 1 | 0.000 | 0.000 | 5.728 | 5.767 | See | See |
KMeans_tall¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: algorithm=full, n_clusters=3, max_iter=30, n_init=1, tol=1e-16.
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | init | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KMeans_tall | fit | 1000000 | 1000000 | 2 | 0.560 | 0.080 | 30 | 0.029 | 0.0 | random | 0.281 | 0.008 | 1.993 | 1.994 | See | See |
| 3 | KMeans_tall | fit | 1000000 | 1000000 | 2 | 0.622 | 0.024 | 30 | 0.026 | 0.0 | k-means++ | 0.314 | 0.007 | 1.979 | 1.980 | See | See |
| 6 | KMeans_tall | fit | 1000000 | 1000000 | 100 | 6.554 | 0.124 | 30 | 0.122 | 0.0 | random | 3.742 | 0.052 | 1.751 | 1.752 | See | See |
| 9 | KMeans_tall | fit | 1000000 | 1000000 | 100 | 6.890 | 0.060 | 30 | 0.116 | 0.0 | k-means++ | 3.914 | 0.027 | 1.760 | 1.760 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | init | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KMeans_tall | predict | 1000000 | 1000 | 2 | 0.002 | 0.001 | 30 | 0.008 | 0.000 | random | 0.0 | 0.0 | 7.769 | 10.130 | See | See |
| 2 | KMeans_tall | predict | 1000000 | 1 | 2 | 0.002 | 0.000 | 30 | 0.000 | 0.002 | random | 0.0 | 0.0 | 10.788 | 10.827 | See | See |
| 4 | KMeans_tall | predict | 1000000 | 1000 | 2 | 0.002 | 0.001 | 30 | 0.008 | 0.000 | k-means++ | 0.0 | 0.0 | 10.770 | 11.079 | See | See |
| 5 | KMeans_tall | predict | 1000000 | 1 | 2 | 0.002 | 0.000 | 30 | 0.000 | 0.002 | k-means++ | 0.0 | 0.0 | 12.224 | 12.281 | See | See |
| 7 | KMeans_tall | predict | 1000000 | 1000 | 100 | 0.002 | 0.000 | 30 | 0.409 | 0.000 | random | 0.0 | 0.0 | 6.909 | 7.060 | See | See |
| 8 | KMeans_tall | predict | 1000000 | 1 | 100 | 0.002 | 0.000 | 30 | 0.001 | 0.002 | random | 0.0 | 0.0 | 9.231 | 9.300 | See | See |
| 10 | KMeans_tall | predict | 1000000 | 1000 | 100 | 0.002 | 0.000 | 30 | 0.407 | 0.000 | k-means++ | 0.0 | 0.0 | 7.503 | 7.704 | See | See |
| 11 | KMeans_tall | predict | 1000000 | 1 | 100 | 0.002 | 0.000 | 30 | 0.000 | 0.002 | k-means++ | 0.0 | 0.0 | 10.183 | 10.447 | See | See |
KMeans_short¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: algorithm=full, n_clusters=300, max_iter=20, n_init=1, tol=1e-16.
| estimator | function | n_samples_train | n_samples | n_features | parameters_digest | dataset_digest | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | algorithm | init | max_iter | n_clusters | n_init | tol | adjusted_rand_score_sklearn | mean_duration_sklearnex | std_duration_sklearnex | adjusted_rand_score_sklearnex | speedup | std_speedup | diff_adjusted_rand_scores | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KMeans_short | predict | 10000 | 1000 | 2 | 3db9c030f488d0e8ff350ae449da4627 | 058b7e3842b587a5c675518f0706f5ee | 0.002129 | 0.000176 | 20 | 0.007515 | 0.000002 | full | random | 20 | 300 | 1 | 1.000000e-16 | 0.000126 | 0.000568 | 0.000093 | -0.000965 | 3.748420 | 3.798222 | 0.001090 |
| 4 | KMeans_short | predict | 10000 | 1000 | 2 | ac9b8cec4749455c0d1cd1a92c150716 | 058b7e3842b587a5c675518f0706f5ee | 0.002147 | 0.000404 | 20 | 0.007451 | 0.000002 | full | k-means++ | 20 | 300 | 1 | 1.000000e-16 | 0.001245 | 0.000648 | 0.000232 | -0.000750 | 3.316129 | 3.522789 | 0.001995 |
| 7 | KMeans_short | predict | 10000 | 1000 | 100 | 3db9c030f488d0e8ff350ae449da4627 | 7f85b913f395ec54101a6738ea63a9a7 | 0.003165 | 0.000222 | 20 | 0.252792 | 0.000003 | full | random | 20 | 300 | 1 | 1.000000e-16 | 0.278733 | 0.001392 | 0.000051 | 0.293767 | 2.273507 | 2.275012 | 0.015034 |
| 10 | KMeans_short | predict | 10000 | 1000 | 100 | ac9b8cec4749455c0d1cd1a92c150716 | 7f85b913f395ec54101a6738ea63a9a7 | 0.002979 | 0.000218 | 20 | 0.268570 | 0.000003 | full | k-means++ | 20 | 300 | 1 | 1.000000e-16 | 0.317011 | 0.001402 | 0.000089 | 0.256968 | 2.124967 | 2.129286 | 0.060044 |
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | init | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KMeans_short | fit | 10000 | 10000 | 2 | 0.095 | 0.004 | 20 | 0.002 | 0.0 | random | 0.050 | 0.003 | 1.917 | 1.920 | See | See |
| 3 | KMeans_short | fit | 10000 | 10000 | 2 | 0.290 | 0.009 | 20 | 0.001 | 0.0 | k-means++ | 0.124 | 0.003 | 2.344 | 2.345 | See | See |
| 6 | KMeans_short | fit | 10000 | 10000 | 100 | 0.319 | 0.011 | 20 | 0.025 | 0.0 | random | 0.251 | 0.006 | 1.275 | 1.275 | See | See |
| 9 | KMeans_short | fit | 10000 | 10000 | 100 | 1.061 | 0.017 | 20 | 0.008 | 0.0 | k-means++ | 0.584 | 0.008 | 1.818 | 1.819 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | init | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KMeans_short | predict | 10000 | 1000 | 2 | 0.002 | 0.0 | 20 | 0.008 | 0.000 | random | 0.001 | 0.0 | 3.748 | 3.798 | See | See |
| 2 | KMeans_short | predict | 10000 | 1 | 2 | 0.002 | 0.0 | 20 | 0.000 | 0.002 | random | 0.000 | 0.0 | 10.099 | 10.293 | See | See |
| 4 | KMeans_short | predict | 10000 | 1000 | 2 | 0.002 | 0.0 | 20 | 0.007 | 0.000 | k-means++ | 0.001 | 0.0 | 3.316 | 3.523 | See | See |
| 5 | KMeans_short | predict | 10000 | 1 | 2 | 0.002 | 0.0 | 20 | 0.000 | 0.002 | k-means++ | 0.000 | 0.0 | 10.868 | 10.981 | See | See |
| 7 | KMeans_short | predict | 10000 | 1000 | 100 | 0.003 | 0.0 | 20 | 0.253 | 0.000 | random | 0.001 | 0.0 | 2.274 | 2.275 | See | See |
| 8 | KMeans_short | predict | 10000 | 1 | 100 | 0.002 | 0.0 | 20 | 0.000 | 0.002 | random | 0.000 | 0.0 | 8.555 | 8.694 | See | See |
| 10 | KMeans_short | predict | 10000 | 1000 | 100 | 0.003 | 0.0 | 20 | 0.269 | 0.000 | k-means++ | 0.001 | 0.0 | 2.125 | 2.129 | See | See |
| 11 | KMeans_short | predict | 10000 | 1 | 100 | 0.002 | 0.0 | 20 | 0.000 | 0.002 | k-means++ | 0.000 | 0.0 | 8.847 | 8.911 | See | See |
LogisticRegression¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: penalty=l2, dual=False, tol=0.0001, C=1.0, fit_intercept=True, intercept_scaling=1, class_weight=nan, random_state=nan, solver=lbfgs, max_iter=100, multi_class=auto, verbose=0, warm_start=False, n_jobs=nan, l1_ratio=nan.
| estimator | function | n_samples_train | n_samples | n_features | parameters_digest | dataset_digest | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | C | class_weight | dual | fit_intercept | intercept_scaling | l1_ratio | max_iter | multi_class | n_jobs | penalty | random_state | solver | tol | verbose | warm_start | accuracy_score_sklearn | mean_duration_sklearnex | std_duration_sklearnex | accuracy_score_sklearnex | speedup | std_speedup | diff_accuracy_scores | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | LogisticRegression | predict | 1000000 | 1000 | 100 | f11be2529b0a77bc8fb5ee8de141e6b2 | 09c36ed6521e03974d0c134895f56c01 | 0.000506 | 0.000442 | [20] | 1.582343 | 5.055793e-07 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0001 | 0 | False | 0.56 | 0.000763 | 0.001259 | 0.55 | 0.662326 | 1.277652 | 0.01 |
| 4 | LogisticRegression | predict | 1000 | 100 | 10000 | f11be2529b0a77bc8fb5ee8de141e6b2 | 7daecaea01e5baa8c862f264e3c1c3b0 | 0.002749 | 0.001288 | [26] | 2.910600 | 2.748574e-05 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0001 | 0 | False | 0.35 | 0.007384 | 0.001184 | 0.28 | 0.372229 | 0.376987 | 0.07 |
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | LogisticRegression | fit | 1000000 | 1000000 | 100 | 15.662 | 0.355 | [20] | 0.051 | 0.000 | 2.802 | 0.063 | 5.589 | 5.591 | See | See |
| 3 | LogisticRegression | fit | 1000 | 1000 | 10000 | 1.416 | 0.730 | [26] | 0.057 | 0.001 | 1.097 | 0.015 | 1.291 | 1.291 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | LogisticRegression | predict | 1000000 | 1000 | 100 | 0.001 | 0.000 | [20] | 1.582 | 0.0 | 0.001 | 0.001 | 0.662 | 1.278 | See | See |
| 2 | LogisticRegression | predict | 1000000 | 1 | 100 | 0.000 | 0.000 | [20] | 0.011 | 0.0 | 0.000 | 0.000 | 0.291 | 0.326 | See | See |
| 4 | LogisticRegression | predict | 1000 | 100 | 10000 | 0.003 | 0.001 | [26] | 2.911 | 0.0 | 0.007 | 0.001 | 0.372 | 0.377 | See | See |
| 5 | LogisticRegression | predict | 1000 | 1 | 10000 | 0.000 | 0.000 | [26] | 0.776 | 0.0 | 0.002 | 0.000 | 0.062 | 0.062 | See | See |
Ridge¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: alpha=1.0, fit_intercept=True, normalize=deprecated, copy_X=True, max_iter=nan, tol=0.001, solver=auto, random_state=nan.
| estimator | function | n_samples_train | n_samples | n_features | parameters_digest | dataset_digest | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | alpha | copy_X | fit_intercept | max_iter | normalize | random_state | solver | tol | r2_score_sklearn | mean_duration_sklearnex | std_duration_sklearnex | r2_score_sklearnex | speedup | std_speedup | diff_r2_scores | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | Ridge | predict | 1000 | 1000 | 10000 | a70ae8dc5c059ec88cf27c61016aee2a | 14fae294d530397144c65ba3209bf125 | 0.011859 | 0.002041 | NaN | 6.745977 | 0.000012 | 1.0 | True | True | NaN | deprecated | NaN | auto | 0.001 | 0.082567 | 0.019529 | 0.002251 | 0.122191 | 0.607255 | 0.611276 | 0.039624 |
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | iteration_throughput | latency | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | Ridge | fit | 1000 | 1000 | 10000 | 0.287 | 0.006 | 0.279 | 0.0 | 0.293 | 0.006 | 0.978 | 0.979 | See | See |
| 3 | Ridge | fit | 1000000 | 1000000 | 100 | 1.250 | 0.078 | 0.640 | 0.0 | 0.416 | 0.242 | 3.005 | 3.476 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | iteration_throughput | latency | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | Ridge | predict | 1000 | 1000 | 10000 | 0.012 | 0.002 | 6.746 | 0.0 | 0.02 | 0.002 | 0.607 | 0.611 | See | See |
| 2 | Ridge | predict | 1000 | 1 | 10000 | 0.000 | 0.000 | 0.867 | 0.0 | 0.00 | 0.000 | 0.637 | 0.654 | See | See |
| 4 | Ridge | predict | 1000000 | 1000 | 100 | 0.000 | 0.000 | 5.180 | 0.0 | 0.00 | 0.000 | 0.410 | 0.677 | See | See |
| 5 | Ridge | predict | 1000000 | 1 | 100 | 0.000 | 0.000 | 0.010 | 0.0 | 0.00 | 0.000 | 0.725 | 0.740 | See | See |